Articles tagged with Computational Science
A team of NTU Singapore scientists has developed a predictive computer programme using wearable technology data to detect depression risk. The programme, Ycogni model, achieves an accuracy of 80% in detecting individuals at high or low risk of depression.
A study by the University of Texas at Austin found that software development teams given greater autonomy are more productive and have higher customer satisfaction rates. The researchers tested 461 projects over 50 months and found a 39% increase in value added for autonomous teams compared to traditional teams.
Professor Alexander Ecker is awarded a Starting Grant to develop machine-learning methods to describe neurons' shape and function, leveraging a large dataset from the US Brain Initiative. The research aims to uncover how a neuron's shape relates to its role in sensory information processing.
A new model suggests that cell-to-cell communication plays a crucial role in determining cell fate, particularly in the development of blood cell types. This finding has significant implications for understanding cancer development and identifying leukemia cells of origin.
Researchers developed a fair-diverse allocation optimization framework to optimize the distribution of COVID-19 vaccines, treatments, and testing supplies. The model aims to get limited resources to the most vulnerable subgroups while ensuring fairness and diversity, independent of demographic background.
A study by researchers at the University of São Paulo developed a model that can predict the likelihood of politicians being convicted of corruption based on their voting histories. The model achieved 90% accuracy in identifying corrupt deputies.
The ATIQ project aims to develop reliable, user-friendly quantum computing demonstrators based on ion trap technology within 30 months. The consortium will optimize hardware for applications in chemistry and finance, paving the way for new approaches in credit risk assessment.
Researchers at the University of Missouri have developed a free online resource that speeds up data analysis of human genomes three times faster than current methods. This enables scientists to see how an individual's genome makes them susceptible to different diseases in different ways, ultimately reducing associated costs and increas...
A team of scientists has created a neural network that can predict and generate new protein structures using deep learning. The network, trained on random protein sequences, can produce stable protein shapes with remarkable accuracy.
A study proposes a new conceptualization framework to characterize music in terms of emotions, enabling better-adapted models for people's characteristics. The research aims to combat the problem of subjectivity and cultural differences in emotion recognition.
A new 'image analysis pipeline' called TDAExplore gives scientists rapid insight into how cells are changed by disease, using a combination of microscopy, topology, and artificial intelligence. This approach can provide objective information on cell changes, such as the movement of proteins like actin, even with limited training data.
Johns Hopkins Medicine researchers have developed a 3D map of blood vessels and stem cells in a mouse skull, revealing previously unknown niches for stem cell residence. The map provides precise locations of blood vessels and stem cells, which could be used to repair wounds and generate new bone tissue.
A new study found that tumors with one mutant copy of the PIK3CA gene tend to have lower PI3K activity, while those with two or more copies often have higher PIK3α activity, leading to more aggressive tumors and poorer prognosis. The research also discovered a counterintuitive relationship between PI3K mutations, PI3K activity, and ste...
A new coil design could mitigate disruption-driven runaway electrons in tokamaks. The SPARC team's innovative coil structure addresses the threat by introducing a non-axisymmetric perturbation that spoils confinement and protects the machine.
Researchers from academia and industry will converge at Lehigh University to discuss innovative solutions for optimizing efficiency and resiliency in the global supply chain. The workshop aims to leverage machine learning for prescriptive analytics, enabling proactive optimization of supply chain operations.
Researchers used computer simulations to predict the presence of hydroxyl radicals, which clean pollutants from the atmosphere. The study showed that traditional models had widely varying forecasts due to uncertainties in gas emissions, and that better models can aid in combating climate change.
A study found that search engines like Yandex and Google often display inaccurate information about health treatments, including false claims about remedy effectiveness. The researchers argue that clearer warnings about possible health risks are needed for medical queries.
Researchers at University of Copenhagen have developed a new quantum circuit that can operate and measure all four qubits simultaneously. This breakthrough resolves a significant engineering headache in the development of large functional quantum computers.
Researchers found that future goals are represented by a pattern of neural activity resembling previous visits, and this activity can re-emerge upon decision to target a location. The orbitofrontal cortex plays a key role in representing future goals during navigation.
A pilot study examines graph-theoretical properties of brain networks in traumatic brain injury and controls, showing association with balance impairment and structural damage. The study uses EEG-based functional connectivity measures during a balance perturbation task to explore underlying neural mechanisms.
Assistant Professor Kang Hao Cheong and his team discovered that chaotic switching for quantum coin Parrondo's games has similar underlying ideas to encryption. They found that using pre-generated chaotic sequences enhances the work, making it easier to invert the encrypted message to obtain the original state.
Researchers at the Salk Institute combined genomic and epidemiological data to reveal that some widespread beliefs about cancer-causing genes are incorrect. For example, KRAS is found to be involved in only about 11% of all cancers, not 25% as previously thought. This study could help guide genetic research for more effective treatments.
A team of researchers from the University of Illinois Urbana-Champaign used advanced machine learning to model the physico-chemical properties of a molten salt compound called FLiNaK, enabling accurate atomic-scale reproduction and prediction of behavior under specific reactor conditions. This computational framework can help character...
The Ohio State University has received a $15 million NSF grant to create the Imageomics Institute, which will use machine learning methodologies to extract biological traits from images. This new approach, called imageomics, aims to transform biomedical, agricultural and basic biological sciences.
Researchers have developed an AI-powered platform that allows scientists to grow virtual tumors and optimize nanoparticle designs using artificial intelligence. The new EVONANO platform has the potential to improve targeted cancer treatments, enabling personalized therapies for individual patients.
Researchers have developed a next-generation reservoir computing that solves complex problems in less than a second, compared to current supercomputers. The new system uses significantly fewer computing resources and less data input, making it 1 million times faster for accurate forecasts.
Researchers at the University of Liverpool have developed a collaborative AI tool that reduces time and effort required to discover new materials. The tool has already led to the discovery of four new materials, including solid state materials with lithium-conductive properties.
BioDynaMo, an open-source simulation platform, enables fast and accurate modeling of complex biological systems. The tool simulates medical cases in neuroscience, oncology, and epidemiology, showcasing its potential for computational biology research.
Researchers designed novel molecules that bound tightly to SARS-CoV-2's molecular scissors, inhibiting the virus's replication. The breakthrough could lead to new treatments for COVID-19.
Researchers at MIT and Institut Pasteur have created an efficient method for assembling entire genomes, including the human genome, in minutes using personal computers. This approach uses minimizer-space de Bruijn graphs to store only a small fraction of nucleotides while preserving overall genome structure, enabling faster processing ...
A team of scientists from Incheon National University developed a programmable DNA-based microfluidic chip that can perform complex mathematical calculations, such as Boolean logic operations. The chip uses a motor-operated valve system to execute a series of reactions in rapid and convenient manner.
Researchers developed a computer model revealing how single brain cells in nematode worms sense and process environmental information to drive decision-making. The study found that sensory cells use salt cues as 'navigation beacons' to direct foraging behavior, controlling the animal's search strategy.
The RIT workshop series on sustainable computing aims to create computers with environmental consciousness from raw materials to recycling. Keynote speakers will discuss trends in computing and its environmental footprint.
Lehigh University researchers are developing a model to understand the impact of grain growth on material properties. The project aims to create new materials informatics methods, innovative stochastic differential equations, and models of grain growth to improve material performance and reliability.
Physicists have developed a new method to identify and address imperfections in materials for quantum computing. The technique, terahertz scanning near-field optical microscopy, has been used to optimize fabrication protocols and reduce decoherence.
Researchers at Technical University of Munich have developed a new machine learning algorithm that can analyze complex markets and their equilibrium strategies. This breakthrough has potential applications in auction theory, wireless spectrum auctions, and more.
A new molecule discovered by researchers at University of Limerick in Ireland enables fast decision-making in computers, breaking the von Neumann bottleneck. The device can solve problems even if individual components fail, providing smaller, faster, and more energy-efficient computing.
Researchers at George Washington University have created a nanophotonic analog processor capable of solving partial differential equations. The processor can process arbitrary inputs at the speed of light and is integrated at chip-scale.
Scientists created a reliable true random number generator using atomically thin two-dimensional films, overcoming long-term stability issues and power consumption concerns. The innovation uses memristors to produce fluctuating electronic signals with an exceptionally high degree of randomness.
Researchers from South Ural State University have conducted a CFD study to analyze droplet flows and determine effective barrier placement in enclosed areas. The approach allows for simulation of real classroom situations, enabling the establishment of strategies to minimize COVID-19 transmission.
Scientists at Carnegie Mellon and University of Washington are developing new software platforms to analyze the Legacy Survey of Space and Time (LSST) dataset. The open-source platforms will enable researchers to make sense of big data and address fundamental questions about the universe, such as dark matter and dark energy.
A new study found that global marine ecosystem models differ widely in their representation of key processes, leading to underestimation of climate change impacts. Marine ecosystem models generally agree on biomass decline but disagree on magnitude and location across the world's oceans through the 21st century.
Scientists at Nara Institute of Science and Technology create a projected touchscreen system using just one camera and projector, eliminating the need for additional detectors. The system uses slope disparity gating to capture touch data with high efficiency, enabling portable projection systems for large interactive displays.
Researchers at University of Illinois and Argonne National Laboratory will explore magnetic materials to reduce noise in quantum computing hardware. The team aims to design non-reciprocal circuitry by harnessing magnetic features, which could lead to a hybrid device for sensing and communication applications.
Quantum engineers at the University of New South Wales have discovered a new technique to control millions of spin qubits, a critical step towards building a practical quantum computer. This breakthrough uses a novel component called a dielectric resonator to focus microwave power and deliver uniform magnetic fields across the chip.
Researchers developed three criteria to assess loss of prediction efficiency when modeling large spatial datasets. The tool, called TLR estimation method, provides insight into 'fit' of approximation parameters and prediction variability.
A team of Beckman researchers developed software to boost infrared imaging-based cancer diagnosis, enhancing image resolution and accelerating recording speeds. The software integrates data analysis and reduces limitations associated with IR imaging, making it faster and more accurate.
Researchers developed a novel evidence-based material recommender system that predicts high entropy alloy formation without data descriptors, overcomes data bias and poor availability. The method recommends an FeMnCoNi alloy as the most probable HEA and successfully synthesizes it, confirming its validity.
Researchers have found that improved learning processes are associated with reduced symptoms of depression. By using brain imaging and mathematical modeling, the team identified distinct paths to depression symptoms and proposed a new approach for treating clinical depression.
A KAUST-led research team has developed an approach to mix high-precision calculations with lower precision for large geospatial datasets, significantly speeding up modeling without overall precision loss. The technique, implemented on high-performance computing systems, will enable larger datasets to be analyzed in shorter timeframes.
Researchers developed a new framework using deep learning techniques to create 3D visualizations from X-ray data. This method is hundreds of times faster than traditional methods, enabling scientists to analyze large amounts of 3D data more efficiently.
A Lehigh University team is working on a culturally tailored program to reduce American Indian smokeless tobacco use, supported by a $1.8 million grant from the American Cancer Society. The All Nations Snuff Out Smokeless (ANSOS) program aims to empower individuals to take control of their health.
Researchers used AI to optimize atomic layer deposition (ALD) processes autonomously, identifying optimal growth conditions for new materials. The study suggests a faster way of converging to optimum combinations without human input, potentially saving manufacturers time and money.
Scientists have created elements comparable to brain neurons and synapses using spins, a magnetic property of electrons. This breakthrough could lead to the development of brain-like computer hardware that can interface with standard silicon-based circuits.
Researchers from the University of Granada and the University of Cádiz have developed a computer system that can help film scriptwriters create successful storylines by analyzing common tropes in films. The system uses artificial intelligence to predict which narrative devices or plot twists are likely to work well with audiences.
Researchers investigate photonics as a solution to develop fast and energy-efficient computing systems inspired by the human brain. By mimicking biological processing systems, they aim to reduce energy losses and improve processor speeds.
Researchers at Lehigh University and Iowa State University have developed a hybrid Cuckoo Search algorithm that accelerates computational modeling of complex alloys by reducing search time up to 13,000-fold. This breakthrough enables the creation of physically realizable systems that can be directly compared against experimental samples.
Computational materials scientists at Ames Laboratory have created an algorithm that uses a hybrid approach inspired by cuckoo birds' nesting habits to find novel high-entropy alloys. The new method significantly reduces the search time for these materials, which are highly sought after for their unique properties and applications.
A study found that visual processing units are identical in size across primate species, from the world's smallest mouse lemur to humans. This preservation suggests an early evolution of primate vision and highlights the importance of conservation efforts for endangered species.
Mathematicians from RUDN University developed new symbolic integration functionality for the Sage system, building on 19th-century ideas by Karl Weierstrass. The team confirmed that Weierstrass's theory can determine whether an integral can be calculated in elementary functions.